Token Classification
Transformers
Safetensors
deberta-v2
information-extraction
places
multilingual
ner
Instructions to use Berk/multilingual-place-extractor-mdeberta-13lang-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Berk/multilingual-place-extractor-mdeberta-13lang-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Berk/multilingual-place-extractor-mdeberta-13lang-tagger", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Berk/multilingual-place-extractor-mdeberta-13lang-tagger") model = AutoModelForTokenClassification.from_pretrained("Berk/multilingual-place-extractor-mdeberta-13lang-tagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle